Functions for performing experimental comparisons of algorithms
using adequate sample sizes for power and accuracy. Implements the
methodology originally presented in Campelo and Takahashi (2019)
Implementation of R package CAISEr, with routines for automatically determining the sample size needed for performing comparative experiments with algorithms.
To install the most up-to-date version directly from Github, simply type:
The most recent CRAN release of the package is also available for installation directly from the R prompt, using:
For instructions and examples of use, please take a look at the vignette
Adapting Algorithms for CAISEr, and at the package documentation, particularly
Please send any bug reports, questions, suggestions, chocolate (to Fernanda) or beers (to Felipe - we can always hope!) directly to the package authors listed at the top of this document.
calc_se()that resulted in
NaNif two vectors with the same sample mean and same sample variance were passed as arguments.
run_experiment()can now be run in parallel using multiple cores.
calc_nreps2()can now save results to files.
run_experiment()now forces the use of all available instances if
power >= 1.
calc_power_curve()to determine the range of effect sizes to consider.